From More-Like-This to Better-Than-This: Hotel Recommendations from User Generated Reviews

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Title: From More-Like-This to Better-Than-This: Hotel Recommendations from User Generated Reviews
Authors: Dong, Ruihai
Smyth, Barry
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Date: 17-Jul-2016
Abstract: To help users discover relevant products and items recommender systems must learn about the likes and dislikes of users and the pros and cons of items. In this paper, we present a novel approach to building rich feature-based user profiles and item descriptions by mining user-generated reviews. We show how this information can be integrated into recommender systems to deliver better recommendations and an improved user experience.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: ACM
Copyright (published version): 2016 the authors
Keywords: Recommender Systems
DOI: 10.1145/2930238.2930276
Language: en
Status of Item: Peer reviewed
Is part of: UMAP '16 Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization
Conference Details: UMAP ’16, Halifax, NS, Canada
Appears in Collections:Insight Research Collection

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